Towards agent-oriented model-driven architecture

Model Driven Architecture supports the transformation from reusable models to executable software. Business representations, however, cannot be fully and explicitly represented in such models for direct transformation into running systems. Thus, once business needs change, the language abstractions used by MDA (e.g. Object Constraint Language / Action Semantics), being low level, have to be edited directly. We therefore describe an Agent-oriented Model Driven Architecture (AMDA) that uses a set of business models under continuous maintenance by business people, reflecting the current business needs and being associated with adaptive agents that interpret the captured knowledge to behave dynamically. Three contributions of the AMDA approach are identified: 1) to Agent-oriented Software Engineering, a method of building adaptive Multi-Agent Systems; 2) to MDA, a means of abstracting high level business-oriented models to align executable systems with their requirements at runtime; 3) to distributed systems, the interoperability of disparate components and services via the agent abstraction.

System oriented neural networks - Problem formulation, methodology and application

A novel methodology is proposed for the development of neural network models for complex engineering systems exhibiting nonlinearity. This method performs neural network modeling by first establishing some fundamental nonlinear functions from a priori engineering knowledge, which are then constructed and coded into appropriate chromosome representations. Given a suitable fitness function, using evolutionary approaches such as genetic algorithms, a population of chromosomes evolves for a certain number of generations to finally produce a neural network model best fitting the system data. The objective is to improve the transparency of the neural networks, i.e. to produce physically meaningful

Value-oriented impact assessment: the economics of a new approach to impact assessment

Environmental Impact Assessment has gained a prominent position as a tool to evaluate the environmental effects of economic activities. However, all approaches proposed so far use a burden-oriented logic. They concentrate on the different environmental impacts in order to ascertain the overall environmental damage caused by economic activity. This paper argues that such a burden-oriented view is (a) hampered by a series of methodological shortcomings which hinders its widespread use in practice; and (b) is analytically incomplete. The paper proposes a value-oriented approach to impact assessment. For this purpose an economic analysis of the optimal use of environmental and social resources is conducted from both a burden-oriented and a value-oriented standpoint. The basic logic of a value-oriented impact assessment is explained, as well as the resulting economic conditions for an optimal use of resources. In addition, it is shown that value- and burden-oriented approaches are complementary to achieve optimality. Finally, the paper discusses the conditions under which the use of burden- or value-oriented impact assessments is appropriate, respectively.

Electrical and Rheological Percolation of PMMA/MWCNT Nanocomposites as a Function of CNT Geometry and Functionality

The ability of carbon nanotubes (CNTs) to reinforce and enhance the electrical conductivity of polymer matrices is a function of both the aspect ratio and surface chemistry of the CNTs. Hitherto, due to the variability in MWCNT synthesis methods it has not been possible to study the effect of MWCNT aspect ratio and functionality on polymer composite properties. This paper was the first to report the correlation between MWCNT aspect ratio and functionality on the formation of electrical and rheological percolated networks. Furthermore, the fundamental ballistic conductance of MWCNTs made using arc discharge and chemical vapour deposition techniques was reported.